Overview

Brought to you by YData

Dataset statistics

Number of variables25
Number of observations60765
Missing cells278339
Missing cells (%)18.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 MiB
Average record size in memory200.0 B

Variable types

Text12
Categorical8
Unsupported3
Numeric2

Alerts

location has constant value "Wien" Constant
classification has constant value "unbekannt; unknown" Constant
repositoryName has constant value "['Albertina', 'Wien, Albertina', 'Albertina']" Constant
relatedWorkNotes has constant value "[]" Constant
earliestDate is highly overall correlated with latestDateHigh correlation
eventType is highly overall correlated with role and 1 other fieldsHigh correlation
latestDate is highly overall correlated with earliestDateHigh correlation
role is highly overall correlated with eventTypeHigh correlation
type is highly overall correlated with eventTypeHigh correlation
type is highly imbalanced (70.6%) Imbalance
role is highly imbalanced (79.7%) Imbalance
rightsStatement is highly imbalanced (97.4%) Imbalance
material has 28334 (46.6%) missing values Missing
displayDate has 60765 (100.0%) missing values Missing
earliestDate has 641 (1.1%) missing values Missing
latestDate has 641 (1.1%) missing values Missing
subject has 60765 (100.0%) missing values Missing
artistName (preferred) has 641 (1.1%) missing values Missing
nationality has 60765 (100.0%) missing values Missing
role has 2691 (4.4%) missing values Missing
birth has 641 (1.1%) missing values Missing
death has 641 (1.1%) missing values Missing
classification has 60733 (99.9%) missing values Missing
lidoRecordId has unique values Unique
workID has unique values Unique
recordID has unique values Unique
recordLinks has unique values Unique
displayDate is an unsupported type, check if it needs cleaning or further analysis Unsupported
subject is an unsupported type, check if it needs cleaning or further analysis Unsupported
nationality is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2025-05-22 08:14:50.982203
Analysis finished2025-05-22 08:15:00.275274
Duration9.29 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

lidoRecordId
Text

Unique 

Distinct60765
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:00.477329image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length28
Median length28
Mean length27.489805
Min length25

Characters and Unicode

Total characters1670418
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60765 ?
Unique (%)100.0%

Sample

1st rowgnd2012512-4/lido/tms_10026
2nd rowgnd2012512-4/lido/tms_10109
3rd rowgnd2012512-4/lido/tms_10150
4th rowgnd2012512-4/lido/tms_101610
5th rowgnd2012512-4/lido/tms_101657
ValueCountFrequency (%)
gnd2012512-4/lido/tms_101745 1
 
< 0.1%
gnd2012512-4/lido/tms_98262 1
 
< 0.1%
gnd2012512-4/lido/tms_10026 1
 
< 0.1%
gnd2012512-4/lido/tms_10109 1
 
< 0.1%
gnd2012512-4/lido/tms_10150 1
 
< 0.1%
gnd2012512-4/lido/tms_101610 1
 
< 0.1%
gnd2012512-4/lido/tms_101657 1
 
< 0.1%
gnd2012512-4/lido/tms_101733 1
 
< 0.1%
gnd2012512-4/lido/tms_101735 1
 
< 0.1%
gnd2012512-4/lido/tms_101736 1
 
< 0.1%
Other values (60755) 60755
> 99.9%
2025-05-22T10:15:00.774374image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 231264
13.8%
1 173251
 
10.4%
d 121530
 
7.3%
/ 121530
 
7.3%
0 92279
 
5.5%
4 91104
 
5.5%
5 88376
 
5.3%
n 60765
 
3.6%
g 60765
 
3.6%
- 60765
 
3.6%
Other values (12) 568789
34.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1670418
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 231264
13.8%
1 173251
 
10.4%
d 121530
 
7.3%
/ 121530
 
7.3%
0 92279
 
5.5%
4 91104
 
5.5%
5 88376
 
5.3%
n 60765
 
3.6%
g 60765
 
3.6%
- 60765
 
3.6%
Other values (12) 568789
34.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1670418
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 231264
13.8%
1 173251
 
10.4%
d 121530
 
7.3%
/ 121530
 
7.3%
0 92279
 
5.5%
4 91104
 
5.5%
5 88376
 
5.3%
n 60765
 
3.6%
g 60765
 
3.6%
- 60765
 
3.6%
Other values (12) 568789
34.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1670418
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 231264
13.8%
1 173251
 
10.4%
d 121530
 
7.3%
/ 121530
 
7.3%
0 92279
 
5.5%
4 91104
 
5.5%
5 88376
 
5.3%
n 60765
 
3.6%
g 60765
 
3.6%
- 60765
 
3.6%
Other values (12) 568789
34.1%
Distinct60280
Distinct (%)99.9%
Missing451
Missing (%)0.7%
Memory size474.9 KiB
2025-05-22T10:15:00.997885image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length8558
Median length5930
Mean length238.38104
Min length212

Characters and Unicode

Total characters14377714
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60254 ?
Unique (%)99.9%

Sample

1st rowhttp://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3276.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3276.JPG
2nd rowhttp://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/13379.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/13379.JPG
3rd rowhttp://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/4281.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/4281.JPG
4th rowhttp://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_106.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_106.JPG
5th rowhttp://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_111.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_111.JPG
ValueCountFrequency (%)
http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/dg1926 108
 
0.1%
vorne.jpg 38
 
< 0.1%
vorne.jpg&width=350 38
 
< 0.1%
hinten.jpg&width=350 35
 
< 0.1%
hinten.jpg 35
 
< 0.1%
http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/12400-12419.jpg 20
 
< 0.1%
http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/12400-12419.jpg&width=350 20
 
< 0.1%
http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/dg1952_460_montage.jpg 12
 
< 0.1%
http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/dg1952_460_montage.jpg&width=350 12
 
< 0.1%
http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/47483_1-12.jpg 12
 
< 0.1%
Other values (121979) 122546
99.7%
2025-05-22T10:15:01.330998image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1104302
 
7.7%
a 1103960
 
7.7%
t 797638
 
5.5%
n 736270
 
5.1%
l 735772
 
5.1%
i 674608
 
4.7%
r 620566
 
4.3%
o 614726
 
4.3%
m 614368
 
4.3%
s 613214
 
4.3%
Other values (63) 6762290
47.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14377714
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1104302
 
7.7%
a 1103960
 
7.7%
t 797638
 
5.5%
n 736270
 
5.1%
l 735772
 
5.1%
i 674608
 
4.7%
r 620566
 
4.3%
o 614726
 
4.3%
m 614368
 
4.3%
s 613214
 
4.3%
Other values (63) 6762290
47.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14377714
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1104302
 
7.7%
a 1103960
 
7.7%
t 797638
 
5.5%
n 736270
 
5.1%
l 735772
 
5.1%
i 674608
 
4.7%
r 620566
 
4.3%
o 614726
 
4.3%
m 614368
 
4.3%
s 613214
 
4.3%
Other values (63) 6762290
47.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14377714
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1104302
 
7.7%
a 1103960
 
7.7%
t 797638
 
5.5%
n 736270
 
5.1%
l 735772
 
5.1%
i 674608
 
4.7%
r 620566
 
4.3%
o 614726
 
4.3%
m 614368
 
4.3%
s 613214
 
4.3%
Other values (63) 6762290
47.0%

type
Categorical

High correlation  Imbalance 

Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
Zeichnung; Zeichnung
36571 
Druckgraphik; Druckgraphik
17307 
Architektur
4265 
Architekturzeichnung; Architekturzeichnung
 
746
Holzstock; Holzstock (Druckstock)
 
733
Other values (33)
 
1143

Length

Max length46
Median length20
Mean length21.569045
Min length5

Characters and Unicode

Total characters1310643
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowZeichnung; Zeichnung
2nd rowZeichnung; Zeichnung
3rd rowZeichnung; Zeichnung
4th rowDruckgraphik; Druckgraphik
5th rowDruckgraphik; Druckgraphik

Common Values

ValueCountFrequency (%)
Zeichnung; Zeichnung 36571
60.2%
Druckgraphik; Druckgraphik 17307
28.5%
Architektur 4265
 
7.0%
Architekturzeichnung; Architekturzeichnung 746
 
1.2%
Holzstock; Holzstock (Druckstock) 733
 
1.2%
Architektur, Entwurf 529
 
0.9%
Architektur, Bauaufnahme 169
 
0.3%
Architektur, Studie, nach 84
 
0.1%
Architektur, Wettbewerbsentwurf 80
 
0.1%
Architektur, Einreichplan 50
 
0.1%
Other values (28) 231
 
0.4%

Length

2025-05-22T10:15:01.441394image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
zeichnung 73142
61.9%
druckgraphik 34615
29.3%
architektur 5330
 
4.5%
architekturzeichnung 1492
 
1.3%
holzstock 1466
 
1.2%
druckstock 733
 
0.6%
entwurf 548
 
0.5%
bauaufnahme 211
 
0.2%
unbekannt 92
 
0.1%
studie 84
 
0.1%
Other values (30) 463
 
0.4%

Most occurring characters

ValueCountFrequency (%)
n 150774
11.5%
c 119209
9.1%
u 118187
9.0%
i 116514
8.9%
h 116484
8.9%
g 109313
8.3%
r 84582
 
6.5%
e 82440
 
6.3%
k 79218
 
6.0%
Z 73142
 
5.6%
Other values (40) 260780
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1310643
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 150774
11.5%
c 119209
9.1%
u 118187
9.0%
i 116514
8.9%
h 116484
8.9%
g 109313
8.3%
r 84582
 
6.5%
e 82440
 
6.3%
k 79218
 
6.0%
Z 73142
 
5.6%
Other values (40) 260780
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1310643
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 150774
11.5%
c 119209
9.1%
u 118187
9.0%
i 116514
8.9%
h 116484
8.9%
g 109313
8.3%
r 84582
 
6.5%
e 82440
 
6.3%
k 79218
 
6.0%
Z 73142
 
5.6%
Other values (40) 260780
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1310643
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 150774
11.5%
c 119209
9.1%
u 118187
9.0%
i 116514
8.9%
h 116484
8.9%
g 109313
8.3%
r 84582
 
6.5%
e 82440
 
6.3%
k 79218
 
6.0%
Z 73142
 
5.6%
Other values (40) 260780
19.9%

material
Text

Missing 

Distinct97
Distinct (%)0.3%
Missing28334
Missing (%)46.6%
Memory size474.9 KiB
2025-05-22T10:15:01.614201image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length222
Median length157
Mean length44.23755
Min length12

Characters and Unicode

Total characters1434668
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st rowFeder; Feder
2nd rowFeder; Feder; laviert; laviert
3rd rowHolzschnitt; Holzschnitt (Druckverfahren)
4th rowHolzschnitt; Holzschnitt (Druckverfahren)
5th rowRadierung; Radierung (Druckverfahren)
ValueCountFrequency (%)
druckverfahren 24528
20.7%
bleistift 18460
15.6%
kupferstich 16608
14.0%
feder 9094
 
7.7%
farblithographie 7948
 
6.7%
holzschnitt 7766
 
6.5%
radierung 6622
 
5.6%
aquarell 6504
 
5.5%
koloriert 3465
 
2.9%
farbe 3252
 
2.7%
Other values (38) 14339
12.1%
2025-05-22T10:15:01.940483image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 146586
 
10.2%
e 145416
 
10.1%
i 98753
 
6.9%
t 91402
 
6.4%
86155
 
6.0%
h 72618
 
5.1%
a 67022
 
4.7%
f 60716
 
4.2%
l 59597
 
4.2%
u 58498
 
4.1%
Other values (41) 547905
38.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1434668
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 146586
 
10.2%
e 145416
 
10.1%
i 98753
 
6.9%
t 91402
 
6.4%
86155
 
6.0%
h 72618
 
5.1%
a 67022
 
4.7%
f 60716
 
4.2%
l 59597
 
4.2%
u 58498
 
4.1%
Other values (41) 547905
38.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1434668
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 146586
 
10.2%
e 145416
 
10.1%
i 98753
 
6.9%
t 91402
 
6.4%
86155
 
6.0%
h 72618
 
5.1%
a 67022
 
4.7%
f 60716
 
4.2%
l 59597
 
4.2%
u 58498
 
4.1%
Other values (41) 547905
38.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1434668
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 146586
 
10.2%
e 145416
 
10.1%
i 98753
 
6.9%
t 91402
 
6.4%
86155
 
6.0%
h 72618
 
5.1%
a 67022
 
4.7%
f 60716
 
4.2%
l 59597
 
4.2%
u 58498
 
4.1%
Other values (41) 547905
38.2%

displayDate
Unsupported

Missing  Rejected  Unsupported 

Missing60765
Missing (%)100.0%
Memory size474.9 KiB

earliestDate
Real number (ℝ)

High correlation  Missing 

Distinct523
Distinct (%)0.9%
Missing641
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean1729.1903
Minimum0
Maximum1991
Zeros205
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:02.057251image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1485
Q11600
median1783
Q31865
95-th percentile1918
Maximum1991
Range1991
Interquartile range (IQR)265

Descriptive statistics

Standard deviation181.43154
Coefficient of variation (CV)0.10492283
Kurtosis25.968368
Mean1729.1903
Median Absolute Deviation (MAD)112
Skewness-3.1530232
Sum1.0396584 × 108
Variance32917.403
MonotonicityNot monotonic
2025-05-22T10:15:02.191947image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1865 1026
 
1.7%
1820 854
 
1.4%
1880 837
 
1.4%
1895 836
 
1.4%
1500 806
 
1.3%
1700 723
 
1.2%
1600 709
 
1.2%
1650 690
 
1.1%
1520 687
 
1.1%
1630 678
 
1.1%
Other values (513) 52278
86.0%
ValueCountFrequency (%)
0 205
0.3%
1100 1
 
< 0.1%
1150 2
 
< 0.1%
1300 3
 
< 0.1%
1310 1
 
< 0.1%
1320 1
 
< 0.1%
1345 1
 
< 0.1%
1352 1
 
< 0.1%
1380 1
 
< 0.1%
1390 1
 
< 0.1%
ValueCountFrequency (%)
1991 1
< 0.1%
1990 2
< 0.1%
1981 1
< 0.1%
1980 2
< 0.1%
1979 1
< 0.1%
1978 1
< 0.1%
1974 1
< 0.1%
1971 1
< 0.1%
1969 1
< 0.1%
1965 1
< 0.1%

latestDate
Real number (ℝ)

High correlation  Missing 

Distinct521
Distinct (%)0.9%
Missing641
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean1746.338
Minimum0
Maximum1996
Zeros371
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:02.330976image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1501
Q11638
median1805
Q31886
95-th percentile1925
Maximum1996
Range1996
Interquartile range (IQR)248

Descriptive statistics

Standard deviation200.76332
Coefficient of variation (CV)0.11496246
Kurtosis32.843541
Mean1746.338
Median Absolute Deviation (MAD)100
Skewness-4.2050566
Sum1.0499683 × 108
Variance40305.91
MonotonicityNot monotonic
2025-05-22T10:15:02.471938image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1914 961
 
1.6%
1900 956
 
1.6%
1905 900
 
1.5%
1800 897
 
1.5%
1889 891
 
1.5%
1822 772
 
1.3%
1550 761
 
1.3%
1500 726
 
1.2%
1865 724
 
1.2%
1910 612
 
1.0%
Other values (511) 51924
85.5%
(Missing) 641
 
1.1%
ValueCountFrequency (%)
0 371
0.6%
1150 1
 
< 0.1%
1200 2
 
< 0.1%
1330 1
 
< 0.1%
1340 1
 
< 0.1%
1355 1
 
< 0.1%
1365 1
 
< 0.1%
1400 3
 
< 0.1%
1415 1
 
< 0.1%
1420 2
 
< 0.1%
ValueCountFrequency (%)
1996 1
 
< 0.1%
1994 6
< 0.1%
1991 1
 
< 0.1%
1990 2
 
< 0.1%
1981 1
 
< 0.1%
1980 2
 
< 0.1%
1979 1
 
< 0.1%
1978 1
 
< 0.1%
1974 1
 
< 0.1%
1971 1
 
< 0.1%

subject
Unsupported

Missing  Rejected  Unsupported 

Missing60765
Missing (%)100.0%
Memory size474.9 KiB
Distinct4752
Distinct (%)7.9%
Missing641
Missing (%)1.1%
Memory size474.9 KiB
2025-05-22T10:15:02.747506image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length80
Median length63
Mean length17.501164
Min length2

Characters and Unicode

Total characters1052240
Distinct characters115
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1958 ?
Unique (%)3.3%

Sample

1st rowBraun, Augustin
2nd rowQuerfurt, August
3rd rowSperling, Catharina
4th rowCranach, Lucas, der Ältere
5th rowCranach, Lucas, der Ältere
ValueCountFrequency (%)
von 5409
 
3.7%
anonym 4712
 
3.2%
carl 3140
 
2.1%
van 2832
 
1.9%
anton 2593
 
1.8%
johann 2435
 
1.7%
hasenauer 1897
 
1.3%
hans 1582
 
1.1%
friedrich 1509
 
1.0%
de 1414
 
1.0%
Other values (5519) 119014
81.2%
2025-05-22T10:15:03.173581image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 90954
 
8.6%
n 86442
 
8.2%
86413
 
8.2%
a 75855
 
7.2%
r 71707
 
6.8%
o 61486
 
5.8%
i 56478
 
5.4%
, 50213
 
4.8%
l 42730
 
4.1%
s 36997
 
3.5%
Other values (105) 392965
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1052240
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 90954
 
8.6%
n 86442
 
8.2%
86413
 
8.2%
a 75855
 
7.2%
r 71707
 
6.8%
o 61486
 
5.8%
i 56478
 
5.4%
, 50213
 
4.8%
l 42730
 
4.1%
s 36997
 
3.5%
Other values (105) 392965
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1052240
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 90954
 
8.6%
n 86442
 
8.2%
86413
 
8.2%
a 75855
 
7.2%
r 71707
 
6.8%
o 61486
 
5.8%
i 56478
 
5.4%
, 50213
 
4.8%
l 42730
 
4.1%
s 36997
 
3.5%
Other values (105) 392965
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1052240
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 90954
 
8.6%
n 86442
 
8.2%
86413
 
8.2%
a 75855
 
7.2%
r 71707
 
6.8%
o 61486
 
5.8%
i 56478
 
5.4%
, 50213
 
4.8%
l 42730
 
4.1%
s 36997
 
3.5%
Other values (105) 392965
37.3%

nationality
Unsupported

Missing  Rejected  Unsupported 

Missing60765
Missing (%)100.0%
Memory size474.9 KiB

role
Categorical

High correlation  Imbalance  Missing 

Distinct22
Distinct (%)< 0.1%
Missing2691
Missing (%)4.4%
Memory size474.9 KiB
Künstler_in
50589 
Druck
 
2517
Zeichner_in
 
1564
Stecher_in
 
952
Entwerfer_in
 
824
Other values (17)
 
1628

Length

Max length30
Median length11
Mean length10.919327
Min length4

Characters and Unicode

Total characters634129
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowKünstler_in
2nd rowKünstler_in
3rd rowKünstler_in
4th rowKünstler_in
5th rowKünstler_in

Common Values

ValueCountFrequency (%)
Künstler_in 50589
83.3%
Druck 2517
 
4.1%
Zeichner_in 1564
 
2.6%
Stecher_in 952
 
1.6%
Entwerfer_in 824
 
1.4%
Formschneider_in 586
 
1.0%
Künstler/in 432
 
0.7%
An der Entstehung Beteiligte_r 256
 
0.4%
Schöpfer_in der Vorlage 189
 
0.3%
Verfasser_in 101
 
0.2%
Other values (12) 64
 
0.1%
(Missing) 2691
 
4.4%

Length

2025-05-22T10:15:03.297009image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
künstler_in 50596
85.3%
druck 2517
 
4.2%
zeichner_in 1569
 
2.6%
stecher_in 952
 
1.6%
entwerfer_in 824
 
1.4%
formschneider_in 586
 
1.0%
der 474
 
0.8%
künstler/in 432
 
0.7%
an 256
 
0.4%
entstehung 256
 
0.4%
Other values (15) 823
 
1.4%

Most occurring characters

ValueCountFrequency (%)
n 110057
17.4%
e 61099
9.6%
r 60313
9.5%
i 57950
9.1%
_ 55104
8.7%
t 53836
8.5%
s 52083
8.2%
l 51518
8.1%
ü 51035
8.0%
K 51028
8.0%
Other values (30) 30106
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 634129
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 110057
17.4%
e 61099
9.6%
r 60313
9.5%
i 57950
9.1%
_ 55104
8.7%
t 53836
8.5%
s 52083
8.2%
l 51518
8.1%
ü 51035
8.0%
K 51028
8.0%
Other values (30) 30106
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 634129
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 110057
17.4%
e 61099
9.6%
r 60313
9.5%
i 57950
9.1%
_ 55104
8.7%
t 53836
8.5%
s 52083
8.2%
l 51518
8.1%
ü 51035
8.0%
K 51028
8.0%
Other values (30) 30106
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 634129
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 110057
17.4%
e 61099
9.6%
r 60313
9.5%
i 57950
9.1%
_ 55104
8.7%
t 53836
8.5%
s 52083
8.2%
l 51518
8.1%
ü 51035
8.0%
K 51028
8.0%
Other values (30) 30106
 
4.7%

birth
Text

Missing 

Distinct1575
Distinct (%)2.6%
Missing641
Missing (%)1.1%
Memory size474.9 KiB
2025-05-22T10:15:03.547254image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.3703346
Min length1

Characters and Unicode

Total characters383010
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique305 ?
Unique (%)0.5%

Sample

1st row1570
2nd row1696
3rd row1699-04-10
4th row1472
5th row1472
ValueCountFrequency (%)
0 7499
 
12.5%
1833 1992
 
3.3%
1480 1617
 
2.7%
1500 1278
 
2.1%
1875-03-22 1192
 
2.0%
1471-05-21 972
 
1.6%
1870-12-10 885
 
1.5%
1870-06-20 877
 
1.5%
1440 654
 
1.1%
1606-07-15 638
 
1.1%
Other values (1565) 42520
70.7%
2025-05-22T10:15:03.909908image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 81870
21.4%
0 60478
15.8%
- 54954
14.3%
8 33599
8.8%
7 28473
 
7.4%
2 27503
 
7.2%
5 20998
 
5.5%
4 20746
 
5.4%
3 19579
 
5.1%
6 19243
 
5.0%
Other values (4) 15567
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 383010
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 81870
21.4%
0 60478
15.8%
- 54954
14.3%
8 33599
8.8%
7 28473
 
7.4%
2 27503
 
7.2%
5 20998
 
5.5%
4 20746
 
5.4%
3 19579
 
5.1%
6 19243
 
5.0%
Other values (4) 15567
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 383010
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 81870
21.4%
0 60478
15.8%
- 54954
14.3%
8 33599
8.8%
7 28473
 
7.4%
2 27503
 
7.2%
5 20998
 
5.5%
4 20746
 
5.4%
3 19579
 
5.1%
6 19243
 
5.0%
Other values (4) 15567
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 383010
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 81870
21.4%
0 60478
15.8%
- 54954
14.3%
8 33599
8.8%
7 28473
 
7.4%
2 27503
 
7.2%
5 20998
 
5.5%
4 20746
 
5.4%
3 19579
 
5.1%
6 19243
 
5.0%
Other values (4) 15567
 
4.1%

death
Text

Missing 

Distinct1659
Distinct (%)2.8%
Missing641
Missing (%)1.1%
Memory size474.9 KiB
2025-05-22T10:15:04.139381image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length21
Median length10
Mean length6.549531
Min length1

Characters and Unicode

Total characters393784
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)0.5%

Sample

1st row1641
2nd row1761
3rd row1741-05-28
4th row1553-10-16
5th row1553-10-16
ValueCountFrequency (%)
0 7680
 
12.8%
1894 1923
 
3.2%
1934-01-07 1192
 
2.0%
1528-04-06 972
 
1.6%
1933-08-12 885
 
1.5%
1940-12-21 877
 
1.5%
1550 856
 
1.4%
1669-10-04 638
 
1.1%
1914-10-30 630
 
1.0%
1667-08-02 605
 
1.0%
Other values (1647) 43876
73.0%
2025-05-22T10:15:04.517518image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 84696
21.5%
- 58746
14.9%
0 58386
14.8%
8 31504
 
8.0%
2 25822
 
6.6%
9 25298
 
6.4%
5 23509
 
6.0%
3 22667
 
5.8%
6 22257
 
5.7%
4 21687
 
5.5%
Other values (17) 19212
 
4.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 393784
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 84696
21.5%
- 58746
14.9%
0 58386
14.8%
8 31504
 
8.0%
2 25822
 
6.6%
9 25298
 
6.4%
5 23509
 
6.0%
3 22667
 
5.8%
6 22257
 
5.7%
4 21687
 
5.5%
Other values (17) 19212
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 393784
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 84696
21.5%
- 58746
14.9%
0 58386
14.8%
8 31504
 
8.0%
2 25822
 
6.6%
9 25298
 
6.4%
5 23509
 
6.0%
3 22667
 
5.8%
6 22257
 
5.7%
4 21687
 
5.5%
Other values (17) 19212
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 393784
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 84696
21.5%
- 58746
14.9%
0 58386
14.8%
8 31504
 
8.0%
2 25822
 
6.6%
9 25298
 
6.4%
5 23509
 
6.0%
3 22667
 
5.8%
6 22257
 
5.7%
4 21687
 
5.5%
Other values (17) 19212
 
4.9%

location
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
Wien
60765 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters243060
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWien
2nd rowWien
3rd rowWien
4th rowWien
5th rowWien

Common Values

ValueCountFrequency (%)
Wien 60765
100.0%

Length

2025-05-22T10:15:04.642807image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-22T10:15:04.753101image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
ValueCountFrequency (%)
wien 60765
100.0%

Most occurring characters

ValueCountFrequency (%)
W 60765
25.0%
i 60765
25.0%
e 60765
25.0%
n 60765
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 243060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
W 60765
25.0%
i 60765
25.0%
e 60765
25.0%
n 60765
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 243060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
W 60765
25.0%
i 60765
25.0%
e 60765
25.0%
n 60765
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 243060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
W 60765
25.0%
i 60765
25.0%
e 60765
25.0%
n 60765
25.0%

title
Text

Distinct45107
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:05.058124image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length380
Median length242
Mean length43.652152
Min length3

Characters and Unicode

Total characters2652523
Distinct characters157
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40263 ?
Unique (%)66.3%

Sample

1st rowRosenkranzmadonna und Anbetung der Könige
2nd rowReiterschlacht
3rd rowModen der Stadt Augsburg (36 Kostümblattentwürfe): Femme sortant en Eté
4th rowDer heilige Christophorus
5th rowVenus und Amor
ValueCountFrequency (%)
der 10777
 
2.9%
mit 10021
 
2.7%
und 9882
 
2.7%
die 7371
 
2.0%
in 5897
 
1.6%
von 4888
 
1.3%
des 4069
 
1.1%
wien 3908
 
1.1%
i 3587
 
1.0%
im 3195
 
0.9%
Other values (41661) 302253
82.6%
2025-05-22T10:15:05.574908image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 306483
 
11.6%
305083
 
11.5%
n 196808
 
7.4%
i 178134
 
6.7%
r 155051
 
5.8%
a 129358
 
4.9%
t 119636
 
4.5%
s 117448
 
4.4%
u 93078
 
3.5%
d 83466
 
3.1%
Other values (147) 967978
36.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2652523
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 306483
 
11.6%
305083
 
11.5%
n 196808
 
7.4%
i 178134
 
6.7%
r 155051
 
5.8%
a 129358
 
4.9%
t 119636
 
4.5%
s 117448
 
4.4%
u 93078
 
3.5%
d 83466
 
3.1%
Other values (147) 967978
36.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2652523
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 306483
 
11.6%
305083
 
11.5%
n 196808
 
7.4%
i 178134
 
6.7%
r 155051
 
5.8%
a 129358
 
4.9%
t 119636
 
4.5%
s 117448
 
4.4%
u 93078
 
3.5%
d 83466
 
3.1%
Other values (147) 967978
36.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2652523
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 306483
 
11.6%
305083
 
11.5%
n 196808
 
7.4%
i 178134
 
6.7%
r 155051
 
5.8%
a 129358
 
4.9%
t 119636
 
4.5%
s 117448
 
4.4%
u 93078
 
3.5%
d 83466
 
3.1%
Other values (147) 967978
36.5%

classification
Categorical

Constant  Missing 

Distinct1
Distinct (%)3.1%
Missing60733
Missing (%)99.9%
Memory size474.9 KiB
unbekannt; unknown
32 

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters576
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowunbekannt; unknown
2nd rowunbekannt; unknown
3rd rowunbekannt; unknown
4th rowunbekannt; unknown
5th rowunbekannt; unknown

Common Values

ValueCountFrequency (%)
unbekannt; unknown 32
 
0.1%
(Missing) 60733
99.9%

Length

2025-05-22T10:15:05.815466image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-22T10:15:05.916943image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
ValueCountFrequency (%)
unbekannt 32
50.0%
unknown 32
50.0%

Most occurring characters

ValueCountFrequency (%)
n 192
33.3%
u 64
 
11.1%
k 64
 
11.1%
b 32
 
5.6%
e 32
 
5.6%
a 32
 
5.6%
t 32
 
5.6%
; 32
 
5.6%
32
 
5.6%
o 32
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 576
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 192
33.3%
u 64
 
11.1%
k 64
 
11.1%
b 32
 
5.6%
e 32
 
5.6%
a 32
 
5.6%
t 32
 
5.6%
; 32
 
5.6%
32
 
5.6%
o 32
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 576
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 192
33.3%
u 64
 
11.1%
k 64
 
11.1%
b 32
 
5.6%
e 32
 
5.6%
a 32
 
5.6%
t 32
 
5.6%
; 32
 
5.6%
32
 
5.6%
o 32
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 576
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 192
33.3%
u 64
 
11.1%
k 64
 
11.1%
b 32
 
5.6%
e 32
 
5.6%
a 32
 
5.6%
t 32
 
5.6%
; 32
 
5.6%
32
 
5.6%
o 32
 
5.6%

rightsStatement
Categorical

Imbalance 

Distinct16
Distinct (%)< 0.1%
Missing451
Missing (%)0.7%
Memory size474.9 KiB
https://creativecommons.org/publicdomain/mark/1.0/
59582 
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/
 
660
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/
 
47
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/
 
8
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/
 
3
Other values (11)
 
14

Length

Max length1818
Median length50
Mean length50.841463
Min length50

Characters and Unicode

Total characters3066452
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowhttps://creativecommons.org/publicdomain/mark/1.0/
2nd rowhttps://creativecommons.org/publicdomain/mark/1.0/
3rd rowhttps://creativecommons.org/publicdomain/mark/1.0/
4th rowhttps://creativecommons.org/publicdomain/mark/1.0/
5th rowhttps://creativecommons.org/publicdomain/mark/1.0/

Common Values

ValueCountFrequency (%)
https://creativecommons.org/publicdomain/mark/1.0/ 59582
98.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 660
 
1.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 47
 
0.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 8
 
< 0.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 3
 
< 0.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 2
 
< 0.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 2
 
< 0.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 2
 
< 0.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 1
 
< 0.1%
https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/ 1
 
< 0.1%
Other values (6) 6
 
< 0.1%
(Missing) 451
 
0.7%

Length

2025-05-22T10:15:06.040257image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://creativecommons.org/publicdomain/mark/1.0 61290
100.0%

Most occurring characters

ValueCountFrequency (%)
/ 367740
 
12.0%
m 245160
 
8.0%
o 245160
 
8.0%
a 183870
 
6.0%
r 183870
 
6.0%
t 183870
 
6.0%
c 183870
 
6.0%
i 183870
 
6.0%
e 122580
 
4.0%
p 122580
 
4.0%
Other values (16) 1043882
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3066452
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 367740
 
12.0%
m 245160
 
8.0%
o 245160
 
8.0%
a 183870
 
6.0%
r 183870
 
6.0%
t 183870
 
6.0%
c 183870
 
6.0%
i 183870
 
6.0%
e 122580
 
4.0%
p 122580
 
4.0%
Other values (16) 1043882
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3066452
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 367740
 
12.0%
m 245160
 
8.0%
o 245160
 
8.0%
a 183870
 
6.0%
r 183870
 
6.0%
t 183870
 
6.0%
c 183870
 
6.0%
i 183870
 
6.0%
e 122580
 
4.0%
p 122580
 
4.0%
Other values (16) 1043882
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3066452
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 367740
 
12.0%
m 245160
 
8.0%
o 245160
 
8.0%
a 183870
 
6.0%
r 183870
 
6.0%
t 183870
 
6.0%
c 183870
 
6.0%
i 183870
 
6.0%
e 122580
 
4.0%
p 122580
 
4.0%
Other values (16) 1043882
34.0%

workID
Text

Unique 

Distinct60765
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:06.197394image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length33
Median length31
Mean length7.2277462
Min length1

Characters and Unicode

Total characters439194
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60765 ?
Unique (%)100.0%

Sample

1st row3276
2nd row13379
3rd row4281
4th rowDG1929/106
5th rowDG1929/111
ValueCountFrequency (%)
vorne 41
 
0.1%
hinten 37
 
0.1%
vorne/verso 6
 
< 0.1%
hinten/verso 5
 
< 0.1%
30307/vorsatz 4
 
< 0.1%
hinten/recto 4
 
< 0.1%
30552/vorsatz 3
 
< 0.1%
30301/vorsatz 3
 
< 0.1%
25934a/deckel 3
 
< 0.1%
16152-74/deckelinnenseite 2
 
< 0.1%
Other values (60735) 60758
99.8%
2025-05-22T10:15:06.520096image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 54647
12.4%
2 46469
10.6%
3 38542
8.8%
0 36073
8.2%
9 34409
 
7.8%
/ 30139
 
6.9%
6 29606
 
6.7%
4 29152
 
6.6%
5 27676
 
6.3%
7 23848
 
5.4%
Other values (51) 88633
20.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 439194
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 54647
12.4%
2 46469
10.6%
3 38542
8.8%
0 36073
8.2%
9 34409
 
7.8%
/ 30139
 
6.9%
6 29606
 
6.7%
4 29152
 
6.6%
5 27676
 
6.3%
7 23848
 
5.4%
Other values (51) 88633
20.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 439194
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 54647
12.4%
2 46469
10.6%
3 38542
8.8%
0 36073
8.2%
9 34409
 
7.8%
/ 30139
 
6.9%
6 29606
 
6.7%
4 29152
 
6.6%
5 27676
 
6.3%
7 23848
 
5.4%
Other values (51) 88633
20.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 439194
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 54647
12.4%
2 46469
10.6%
3 38542
8.8%
0 36073
8.2%
9 34409
 
7.8%
/ 30139
 
6.9%
6 29606
 
6.7%
4 29152
 
6.6%
5 27676
 
6.3%
7 23848
 
5.4%
Other values (51) 88633
20.2%

repositoryName
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
['Albertina', 'Wien, Albertina', 'Albertina']
60765 

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters2734425
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row['Albertina', 'Wien, Albertina', 'Albertina']
2nd row['Albertina', 'Wien, Albertina', 'Albertina']
3rd row['Albertina', 'Wien, Albertina', 'Albertina']
4th row['Albertina', 'Wien, Albertina', 'Albertina']
5th row['Albertina', 'Wien, Albertina', 'Albertina']

Common Values

ValueCountFrequency (%)
['Albertina', 'Wien, Albertina', 'Albertina'] 60765
100.0%

Length

2025-05-22T10:15:06.613920image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-22T10:15:06.689217image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
ValueCountFrequency (%)
albertina 182295
75.0%
wien 60765
 
25.0%

Most occurring characters

ValueCountFrequency (%)
' 364590
13.3%
e 243060
8.9%
i 243060
8.9%
n 243060
8.9%
l 182295
 
6.7%
b 182295
 
6.7%
A 182295
 
6.7%
, 182295
 
6.7%
r 182295
 
6.7%
t 182295
 
6.7%
Other values (5) 546885
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2734425
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 364590
13.3%
e 243060
8.9%
i 243060
8.9%
n 243060
8.9%
l 182295
 
6.7%
b 182295
 
6.7%
A 182295
 
6.7%
, 182295
 
6.7%
r 182295
 
6.7%
t 182295
 
6.7%
Other values (5) 546885
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2734425
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 364590
13.3%
e 243060
8.9%
i 243060
8.9%
n 243060
8.9%
l 182295
 
6.7%
b 182295
 
6.7%
A 182295
 
6.7%
, 182295
 
6.7%
r 182295
 
6.7%
t 182295
 
6.7%
Other values (5) 546885
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2734425
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 364590
13.3%
e 243060
8.9%
i 243060
8.9%
n 243060
8.9%
l 182295
 
6.7%
b 182295
 
6.7%
A 182295
 
6.7%
, 182295
 
6.7%
r 182295
 
6.7%
t 182295
 
6.7%
Other values (5) 546885
20.0%

recordID
Text

Unique 

Distinct60765
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:06.933753image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.489805
Min length7

Characters and Unicode

Total characters576648
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60765 ?
Unique (%)100.0%

Sample

1st rowtms_10026
2nd rowtms_10109
3rd rowtms_10150
4th rowtms_101610
5th rowtms_101657
ValueCountFrequency (%)
tms_101745 1
 
< 0.1%
tms_98262 1
 
< 0.1%
tms_10026 1
 
< 0.1%
tms_10109 1
 
< 0.1%
tms_10150 1
 
< 0.1%
tms_101610 1
 
< 0.1%
tms_101657 1
 
< 0.1%
tms_101733 1
 
< 0.1%
tms_101735 1
 
< 0.1%
tms_101736 1
 
< 0.1%
Other values (60755) 60755
> 99.9%
2025-05-22T10:15:07.402137image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 60765
10.5%
m 60765
10.5%
s 60765
10.5%
_ 60765
10.5%
1 51721
9.0%
2 48969
8.5%
3 38508
 
6.7%
0 31514
 
5.5%
4 30339
 
5.3%
8 28299
 
4.9%
Other values (4) 104238
18.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 576648
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 60765
10.5%
m 60765
10.5%
s 60765
10.5%
_ 60765
10.5%
1 51721
9.0%
2 48969
8.5%
3 38508
 
6.7%
0 31514
 
5.5%
4 30339
 
5.3%
8 28299
 
4.9%
Other values (4) 104238
18.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 576648
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 60765
10.5%
m 60765
10.5%
s 60765
10.5%
_ 60765
10.5%
1 51721
9.0%
2 48969
8.5%
3 38508
 
6.7%
0 31514
 
5.5%
4 30339
 
5.3%
8 28299
 
4.9%
Other values (4) 104238
18.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 576648
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 60765
10.5%
m 60765
10.5%
s 60765
10.5%
_ 60765
10.5%
1 51721
9.0%
2 48969
8.5%
3 38508
 
6.7%
0 31514
 
5.5%
4 30339
 
5.3%
8 28299
 
4.9%
Other values (4) 104238
18.1%

recordLinks
Text

Unique 

Distinct60765
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:07.616812image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length114
Median length112
Mean length88.227746
Min length82

Characters and Unicode

Total characters5361159
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60765 ?
Unique (%)100.0%

Sample

1st row['http://sammlungenonline.albertina.at/?query=Inventarnummer=[3276]&showtype=record']
2nd row['http://sammlungenonline.albertina.at/?query=Inventarnummer=[13379]&showtype=record']
3rd row['http://sammlungenonline.albertina.at/?query=Inventarnummer=[4281]&showtype=record']
4th row['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1929/106]&showtype=record']
5th row['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1929/111]&showtype=record']
ValueCountFrequency (%)
vorne]&showtype=record 40
 
0.1%
hinten]&showtype=record 37
 
0.1%
vorne/verso]&showtype=record 6
 
< 0.1%
hinten/verso]&showtype=record 5
 
< 0.1%
hinten/recto]&showtype=record 4
 
< 0.1%
http://sammlungenonline.albertina.at/?query=inventarnummer=[30307/vorsatz 4
 
< 0.1%
http://sammlungenonline.albertina.at/?query=inventarnummer=[30301/vorsatz 3
 
< 0.1%
http://sammlungenonline.albertina.at/?query=inventarnummer=[30552/vorsatz 3
 
< 0.1%
http://sammlungenonline.albertina.at/?query=inventarnummer=[25934a/deckel 3
 
< 0.1%
http://sammlungenonline.albertina.at/?query=inventarnummer=[26866/umschlag 2
 
< 0.1%
Other values (60736) 60759
99.8%
2025-05-22T10:15:07.935222image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 486580
 
9.1%
n 486459
 
9.1%
r 368725
 
6.9%
t 364824
 
6.8%
a 304131
 
5.7%
m 243762
 
4.5%
/ 212434
 
4.0%
o 183156
 
3.4%
l 182418
 
3.4%
u 182325
 
3.4%
Other values (58) 2346345
43.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5361159
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 486580
 
9.1%
n 486459
 
9.1%
r 368725
 
6.9%
t 364824
 
6.8%
a 304131
 
5.7%
m 243762
 
4.5%
/ 212434
 
4.0%
o 183156
 
3.4%
l 182418
 
3.4%
u 182325
 
3.4%
Other values (58) 2346345
43.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5361159
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 486580
 
9.1%
n 486459
 
9.1%
r 368725
 
6.9%
t 364824
 
6.8%
a 304131
 
5.7%
m 243762
 
4.5%
/ 212434
 
4.0%
o 183156
 
3.4%
l 182418
 
3.4%
u 182325
 
3.4%
Other values (58) 2346345
43.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5361159
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 486580
 
9.1%
n 486459
 
9.1%
r 368725
 
6.9%
t 364824
 
6.8%
a 304131
 
5.7%
m 243762
 
4.5%
/ 212434
 
4.0%
o 183156
 
3.4%
l 182418
 
3.4%
u 182325
 
3.4%
Other values (58) 2346345
43.8%

eventType
Categorical

High correlation 

Distinct5
Distinct (%)< 0.1%
Missing179
Missing (%)0.3%
Memory size474.9 KiB
Production
41790 
Expression Creation
13425 
Carrier production
 
3797
Work conception
 
1112
Provenienz
 
462

Length

Max length19
Median length10
Mean length12.587413
Min length10

Characters and Unicode

Total characters762621
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowProduction
2nd rowProduction
3rd rowProduction
4th rowExpression Creation
5th rowExpression Creation

Common Values

ValueCountFrequency (%)
Production 41790
68.8%
Expression Creation 13425
 
22.1%
Carrier production 3797
 
6.2%
Work conception 1112
 
1.8%
Provenienz 462
 
0.8%
(Missing) 179
 
0.3%

Length

2025-05-22T10:15:08.041991image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-22T10:15:08.155219image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
ValueCountFrequency (%)
production 45587
57.8%
expression 13425
 
17.0%
creation 13425
 
17.0%
carrier 3797
 
4.8%
work 1112
 
1.4%
conception 1112
 
1.4%
provenienz 462
 
0.6%

Most occurring characters

ValueCountFrequency (%)
o 121822
16.0%
r 85402
11.2%
i 77808
10.2%
n 75585
9.9%
t 60124
7.9%
c 47811
 
6.3%
d 45587
 
6.0%
u 45587
 
6.0%
P 42252
 
5.5%
e 32683
 
4.3%
Other values (11) 127960
16.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 762621
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 121822
16.0%
r 85402
11.2%
i 77808
10.2%
n 75585
9.9%
t 60124
7.9%
c 47811
 
6.3%
d 45587
 
6.0%
u 45587
 
6.0%
P 42252
 
5.5%
e 32683
 
4.3%
Other values (11) 127960
16.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 762621
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 121822
16.0%
r 85402
11.2%
i 77808
10.2%
n 75585
9.9%
t 60124
7.9%
c 47811
 
6.3%
d 45587
 
6.0%
u 45587
 
6.0%
P 42252
 
5.5%
e 32683
 
4.3%
Other values (11) 127960
16.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 762621
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 121822
16.0%
r 85402
11.2%
i 77808
10.2%
n 75585
9.9%
t 60124
7.9%
c 47811
 
6.3%
d 45587
 
6.0%
u 45587
 
6.0%
P 42252
 
5.5%
e 32683
 
4.3%
Other values (11) 127960
16.8%
Distinct13955
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:08.386849image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length444
Median length348
Mean length35.645849
Min length2

Characters and Unicode

Total characters2166020
Distinct characters92
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11109 ?
Unique (%)18.3%

Sample

1st row['Tusche, Feder, laviert']
2nd row['Rötel, Feder in Braun mit Graulavierungen']
3rd row['Feder in Grau, laviert']
4th row['Holzschnitt']
5th row['Holzschnitt']
ValueCountFrequency (%)
feder 15422
 
6.5%
in 15016
 
6.4%
bleistift 13732
 
5.8%
laviert 9130
 
3.9%
und 7366
 
3.1%
braun 6750
 
2.9%
kreide 6362
 
2.7%
papier 6068
 
2.6%
kupferstich 5823
 
2.5%
grau 5351
 
2.3%
Other values (4675) 144793
61.4%
2025-05-22T10:15:08.753324image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 220343
 
10.2%
175048
 
8.1%
i 159306
 
7.4%
r 149054
 
6.9%
' 129063
 
6.0%
t 118498
 
5.5%
a 105701
 
4.9%
n 99849
 
4.6%
l 86918
 
4.0%
u 74270
 
3.4%
Other values (82) 847970
39.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2166020
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 220343
 
10.2%
175048
 
8.1%
i 159306
 
7.4%
r 149054
 
6.9%
' 129063
 
6.0%
t 118498
 
5.5%
a 105701
 
4.9%
n 99849
 
4.6%
l 86918
 
4.0%
u 74270
 
3.4%
Other values (82) 847970
39.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2166020
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 220343
 
10.2%
175048
 
8.1%
i 159306
 
7.4%
r 149054
 
6.9%
' 129063
 
6.0%
t 118498
 
5.5%
a 105701
 
4.9%
n 99849
 
4.6%
l 86918
 
4.0%
u 74270
 
3.4%
Other values (82) 847970
39.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2166020
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 220343
 
10.2%
175048
 
8.1%
i 159306
 
7.4%
r 149054
 
6.9%
' 129063
 
6.0%
t 118498
 
5.5%
a 105701
 
4.9%
n 99849
 
4.6%
l 86918
 
4.0%
u 74270
 
3.4%
Other values (82) 847970
39.1%
Distinct16804
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
2025-05-22T10:15:09.064088image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length2927
Median length1248
Mean length35.781042
Min length2

Characters and Unicode

Total characters2174235
Distinct characters156
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15041 ?
Unique (%)24.8%

Sample

1st row['M.u. "Anno 1614. AB"']
2nd row['l. u. Herzog Albert von Sachsen-Teschen (Lugt 174)']
3rd row['l. u. Herzog Albert von Sachsen-Teschen (Lugt 174)']
4th row['l.o. "L C" mit Schlangensignet']
5th row['r.o. "L / 1506 / C"']
ValueCountFrequency (%)
40741
 
12.3%
l.u 16759
 
5.0%
von 14105
 
4.2%
albert 12959
 
3.9%
lugt 12827
 
3.9%
sachsen-teschen 12753
 
3.8%
herzog 12546
 
3.8%
174 12318
 
3.7%
r.u 10570
 
3.2%
in 4791
 
1.4%
Other values (23989) 182013
54.8%
2025-05-22T10:15:09.499490image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
271617
 
12.5%
e 154439
 
7.1%
. 118468
 
5.4%
r 96036
 
4.4%
n 88031
 
4.0%
' 84658
 
3.9%
u 75083
 
3.5%
t 73013
 
3.4%
" 66791
 
3.1%
l 65056
 
3.0%
Other values (146) 1081043
49.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2174235
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
271617
 
12.5%
e 154439
 
7.1%
. 118468
 
5.4%
r 96036
 
4.4%
n 88031
 
4.0%
' 84658
 
3.9%
u 75083
 
3.5%
t 73013
 
3.4%
" 66791
 
3.1%
l 65056
 
3.0%
Other values (146) 1081043
49.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2174235
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
271617
 
12.5%
e 154439
 
7.1%
. 118468
 
5.4%
r 96036
 
4.4%
n 88031
 
4.0%
' 84658
 
3.9%
u 75083
 
3.5%
t 73013
 
3.4%
" 66791
 
3.1%
l 65056
 
3.0%
Other values (146) 1081043
49.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2174235
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
271617
 
12.5%
e 154439
 
7.1%
. 118468
 
5.4%
r 96036
 
4.4%
n 88031
 
4.0%
' 84658
 
3.9%
u 75083
 
3.5%
t 73013
 
3.4%
" 66791
 
3.1%
l 65056
 
3.0%
Other values (146) 1081043
49.7%

relatedWorkNotes
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size474.9 KiB
[]
60765 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters121530
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[]
2nd row[]
3rd row[]
4th row[]
5th row[]

Common Values

ValueCountFrequency (%)
[] 60765
100.0%

Length

2025-05-22T10:15:09.645268image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-22T10:15:09.725318image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
ValueCountFrequency (%)
60765
100.0%

Most occurring characters

ValueCountFrequency (%)
[ 60765
50.0%
] 60765
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 121530
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
[ 60765
50.0%
] 60765
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 121530
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
[ 60765
50.0%
] 60765
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 121530
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
[ 60765
50.0%
] 60765
50.0%

Interactions

2025-05-22T10:14:58.523799image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
2025-05-22T10:14:58.289650image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
2025-05-22T10:14:58.625643image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
2025-05-22T10:14:58.403477image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Correlations

2025-05-22T10:15:09.769623image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
earliestDateeventTypelatestDaterightsStatementroletype
earliestDate1.0000.3150.9710.1490.1500.281
eventType0.3151.0000.3240.0380.7610.560
latestDate0.9710.3241.0000.0280.1460.291
rightsStatement0.1490.0380.0281.0000.0330.023
role0.1500.7610.1460.0331.0000.277
type0.2810.5600.2910.0230.2771.000

Missing values

2025-05-22T10:14:58.837766image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-22T10:14:59.290691image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-05-22T10:14:59.965759image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

lidoRecordIdimageUrltypematerialdisplayDateearliestDatelatestDatesubjectartistName (preferred)nationalityrolebirthdeathlocationtitleclassificationrightsStatementworkIDrepositoryNamerecordIDrecordLinkseventTypedisplayMaterialsTechinscriptionsrelatedWorkNotes
0gnd2012512-4/lido/tms_10026http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3276.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3276.JPGZeichnung; ZeichnungFeder; FederNaN1614.01614.0NaNBraun, AugustinNaNKünstler_in15701641WienRosenkranzmadonna und Anbetung der KönigeNaNhttps://creativecommons.org/publicdomain/mark/1.0/3276['Albertina', 'Wien, Albertina', 'Albertina']tms_10026['http://sammlungenonline.albertina.at/?query=Inventarnummer=[3276]&showtype=record']Production['Tusche, Feder, laviert']['M.u. "Anno 1614. AB"'][]
1gnd2012512-4/lido/tms_10109http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/13379.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/13379.JPGZeichnung; ZeichnungNaNNaN1716.01761.0NaNQuerfurt, AugustNaNKünstler_in16961761WienReiterschlachtNaNhttps://creativecommons.org/publicdomain/mark/1.0/13379['Albertina', 'Wien, Albertina', 'Albertina']tms_10109['http://sammlungenonline.albertina.at/?query=Inventarnummer=[13379]&showtype=record']Production['Rötel, Feder in Braun mit Graulavierungen']['l. u. Herzog Albert von Sachsen-Teschen (Lugt 174)'][]
2gnd2012512-4/lido/tms_10150http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/4281.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/4281.JPGZeichnung; ZeichnungFeder; Feder; laviert; laviertNaN1719.01741.0NaNSperling, CatharinaNaNKünstler_in1699-04-101741-05-28WienModen der Stadt Augsburg (36 Kostümblattentwürfe): Femme sortant en EtéNaNhttps://creativecommons.org/publicdomain/mark/1.0/4281['Albertina', 'Wien, Albertina', 'Albertina']tms_10150['http://sammlungenonline.albertina.at/?query=Inventarnummer=[4281]&showtype=record']Production['Feder in Grau, laviert']['l. u. Herzog Albert von Sachsen-Teschen (Lugt 174)'][]
3gnd2012512-4/lido/tms_101610http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_106.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_106.JPGDruckgraphik; DruckgraphikHolzschnitt; Holzschnitt (Druckverfahren)NaN1506.01554.0NaNCranach, Lucas, der ÄltereNaNKünstler_in14721553-10-16WienDer heilige ChristophorusNaNhttps://creativecommons.org/publicdomain/mark/1.0/DG1929/106['Albertina', 'Wien, Albertina', 'Albertina']tms_101610['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1929/106]&showtype=record']Expression Creation['Holzschnitt']['l.o. "L C" mit Schlangensignet'][]
4gnd2012512-4/lido/tms_101657http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_111.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1929_111.JPGDruckgraphik; DruckgraphikHolzschnitt; Holzschnitt (Druckverfahren)NaN1506.01506.0NaNCranach, Lucas, der ÄltereNaNKünstler_in14721553-10-16WienVenus und AmorNaNhttps://creativecommons.org/publicdomain/mark/1.0/DG1929/111['Albertina', 'Wien, Albertina', 'Albertina']tms_101657['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1929/111]&showtype=record']Expression Creation['Holzschnitt']['r.o. "L / 1506 / C"'][]
5gnd2012512-4/lido/tms_101733http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1749.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1749.jpgDruckgraphik; DruckgraphikRadierung; Radierung (Druckverfahren)NaN1514.01524.0NaNAltdorfer, AlbrechtNaNKünstler_in14801538-02-12WienDas Innere der Regensburger SynagogeNaNhttps://creativecommons.org/publicdomain/mark/1.0/DG1926/1749['Albertina', 'Wien, Albertina', 'Albertina']tms_101733['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1926/1749]&showtype=record']Expression Creation['Radierung']['M.u. "AA", in der Inschrift ".D.XIX."'][]
6gnd2012512-4/lido/tms_101735http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1701.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1701.jpgDruckgraphik; DruckgraphikKupferstich; Kupferstich (Druckverfahren); Kupferstich (Druckverfahren)NaN1514.01524.0NaNAltdorfer, AlbrechtNaNKünstler_in14801538-02-12WienMaria sucht ihren Sohn in der SynagogeNaNhttps://creativecommons.org/publicdomain/mark/1.0/DG1926/1701['Albertina', 'Wien, Albertina', 'Albertina']tms_101735['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1926/1701]&showtype=record']Expression Creation['Kupferstich']['r.u. "AA"'][]
7gnd2012512-4/lido/tms_101736http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1700.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1700.jpgDruckgraphik; DruckgraphikKupferstich; Kupferstich (Druckverfahren); Kupferstich (Druckverfahren)NaN1507.01517.0NaNAltdorfer, AlbrechtNaNKünstler_in14801538-02-12WienDer heilige Sebastian, an eine Säule gebundenNaNhttps://creativecommons.org/publicdomain/mark/1.0/DG1926/1700['Albertina', 'Wien, Albertina', 'Albertina']tms_101736['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1926/1700]&showtype=record']Expression Creation['Kupferstich']['l.u. "AA"'][]
8gnd2012512-4/lido/tms_101737http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1703.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1703.jpgDruckgraphik; DruckgraphikKupferstich; Kupferstich (Druckverfahren); Kupferstich (Druckverfahren)NaN1515.01525.0NaNAltdorfer, AlbrechtNaNKünstler_in14801538-02-12WienHoratius Cocles springt in den TiberNaNhttps://creativecommons.org/publicdomain/mark/1.0/DG1926/1703['Albertina', 'Wien, Albertina', 'Albertina']tms_101737['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1926/1703]&showtype=record']Expression Creation['Kupferstich']['l.u. "AA"'][]
9gnd2012512-4/lido/tms_101738http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1704.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/DG1926_1704.jpgDruckgraphik; DruckgraphikKupferstich; Kupferstich (Druckverfahren); Kupferstich (Druckverfahren)NaN1515.01525.0NaNAltdorfer, AlbrechtNaNKünstler_in14801538-02-12WienNeptun, auf einer Meeresschlange liegendNaNhttps://creativecommons.org/publicdomain/mark/1.0/DG1926/1704['Albertina', 'Wien, Albertina', 'Albertina']tms_101738['http://sammlungenonline.albertina.at/?query=Inventarnummer=[DG1926/1704]&showtype=record']Expression Creation['Kupferstich']['r.u. "AA"'][]
lidoRecordIdimageUrltypematerialdisplayDateearliestDatelatestDatesubjectartistName (preferred)nationalityrolebirthdeathlocationtitleclassificationrightsStatementworkIDrepositoryNamerecordIDrecordLinkseventTypedisplayMaterialsTechinscriptionsrelatedWorkNotes
60755gnd2012512-4/lido/tms_97145http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25953_1.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25953_1.jpgZeichnung; ZeichnungBleistift; BleistiftNaN1820.01865.0NaNWaldmüller, Ferdinand GeorgNaNKünstler_in1793-01-151865-08-23WienVerschiedene SkizzenNaNhttps://creativecommons.org/publicdomain/mark/1.0/25953/1['Albertina', 'Wien, Albertina', 'Albertina']tms_97145['http://sammlungenonline.albertina.at/?query=Inventarnummer=[25953/1]&showtype=record']Production['Bleistift'][][]
60756gnd2012512-4/lido/tms_97147http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25951_1.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25951_1.jpgZeichnung; ZeichnungBleistift; BleistiftNaN1829.01829.0NaNWaldmüller, Ferdinand GeorgNaNKünstler_in1793-01-151865-08-23WienVerschiedene SkizzenNaNhttps://creativecommons.org/publicdomain/mark/1.0/25951/1['Albertina', 'Wien, Albertina', 'Albertina']tms_97147['http://sammlungenonline.albertina.at/?query=Inventarnummer=[25951/1]&showtype=record']Production['Bleistift'][][]
60757gnd2012512-4/lido/tms_97148http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25952_1.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25952_1.jpgZeichnung; ZeichnungBleistift; BleistiftNaN1820.01865.0NaNWaldmüller, Ferdinand GeorgNaNKünstler_in1793-01-151865-08-23WienVerschiedene SkizzenNaNhttps://creativecommons.org/publicdomain/mark/1.0/25952/1['Albertina', 'Wien, Albertina', 'Albertina']tms_97148['http://sammlungenonline.albertina.at/?query=Inventarnummer=[25952/1]&showtype=record']Production['Bleistift'][][]
60758gnd2012512-4/lido/tms_97149http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25947_1.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25947_1.jpgZeichnung; ZeichnungBleistift; BleistiftNaN1820.01865.0NaNWaldmüller, Ferdinand GeorgNaNKünstler_in1793-01-151865-08-23WienVerschiedene SkizzenNaNhttps://creativecommons.org/publicdomain/mark/1.0/25947/1['Albertina', 'Wien, Albertina', 'Albertina']tms_97149['http://sammlungenonline.albertina.at/?query=Inventarnummer=[25947/1]&showtype=record']Production['Bleistift'][][]
60759gnd2012512-4/lido/tms_97150http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25949_1.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/25949_1.jpgZeichnung; ZeichnungBleistift; BleistiftNaN1820.01865.0NaNWaldmüller, Ferdinand GeorgNaNKünstler_in1793-01-151865-08-23WienVerschiedene SkizzenNaNhttps://creativecommons.org/publicdomain/mark/1.0/25949/1['Albertina', 'Wien, Albertina', 'Albertina']tms_97150['http://sammlungenonline.albertina.at/?query=Inventarnummer=[25949/1]&showtype=record']Production['Bleistift'][][]
60760gnd2012512-4/lido/tms_9765http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3417.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3417.JPGZeichnung; ZeichnungFeder; FederNaN1634.01634.0NaNWagner, ValentinNaNKünstler_in16101655WienReiseskizzenbuch: Hans Anton Porges schläft auf einem BauernsesselNaNhttps://creativecommons.org/publicdomain/mark/1.0/3417['Albertina', 'Wien, Albertina', 'Albertina']tms_9765['http://sammlungenonline.albertina.at/?query=Inventarnummer=[3417]&showtype=record']Production['Feder in Braun']['r.o. "Franckfortt am Maijn 1634"', 'l.o. "Hans Anthon porges"'][]
60761gnd2012512-4/lido/tms_9766http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3418R.JPG&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/3418R.JPGZeichnung; ZeichnungNaNNaN1634.01634.0NaNWagner, ValentinNaNKünstler_in16101655WienReiseskizzenbuch: Mann und Frau schlafend neben einem WandbrunnenNaNhttps://creativecommons.org/publicdomain/mark/1.0/3418r['Albertina', 'Wien, Albertina', 'Albertina']tms_9766['http://sammlungenonline.albertina.at/?query=Inventarnummer=[3418r]&showtype=record']Production['Feder in lichtem Graubraun']['M.o. "Fecit dresden Ao 1634"'][]
60762gnd2012512-4/lido/tms_98259http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_a.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_a.jpgZeichnung; ZeichnungFeder; Feder; laviert; laviert; Feder; Feder; laviert; laviertNaN1776.01776.0NaNAnonymNaNSchreiber_in00WienDiscorso Preliminare, Widmungsblatt an Herzog AlbertNaNhttps://creativecommons.org/publicdomain/mark/1.0/30858a['Albertina', 'Wien, Albertina', 'Albertina']tms_98259['http://sammlungenonline.albertina.at/?query=Inventarnummer=[30858a]&showtype=record']Production['Feder, laviert', 'Feder, laviert'][][]
60763gnd2012512-4/lido/tms_98260http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_f.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_f.jpg; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_fv.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_fv.jpgZeichnung; ZeichnungFeder; FederNaN1776.00.0NaNDurazzo, GiacomoNaNKünstler_in1717-04-271794-10-15WienDiscorso Preliminare, Schlussblatt "Degli Indici della Raccolta" (mit "Nota" rückseitig, nach 1792)NaNhttps://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/30858f['Albertina', 'Wien, Albertina', 'Albertina']tms_98260['http://sammlungenonline.albertina.at/?query=Inventarnummer=[30858f]&showtype=record']Production['Feder'][][]
60764gnd2012512-4/lido/tms_98262http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_c.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_c.jpg; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_cv.jpg&width=350; http://sammlungenonline.albertina.at/cc/imageproxy.ashx?server=localhost&port=15001&filename=images/30858_cv.jpgZeichnung; ZeichnungFeder; FederNaN1776.00.0NaNDurazzo, GiacomoNaNKünstler_in1717-04-271794-10-15WienDiscorso Preliminare, 2. TextseiteNaNhttps://creativecommons.org/publicdomain/mark/1.0/; https://creativecommons.org/publicdomain/mark/1.0/30858c['Albertina', 'Wien, Albertina', 'Albertina']tms_98262['http://sammlungenonline.albertina.at/?query=Inventarnummer=[30858c]&showtype=record']Production['Feder'][][]